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Datafication is a technological trend turning many aspects of our life into data[1] which is subsequently transferred into information realised as a new form of value.[2] Kenneth Cukier and Victor Mayer-Schöenberger introduced the term Datafication to the broader lexicon in 2013.[3] Up until this time, datafication had been associated with the analysis of representations of our lives captured through data, but not on the present scale. This change was primarily due to the impact of big data and the computational opportunities afforded to predictive analytics.


Examples of datafication as applied to social and communication media are how Twitter datafies stray thoughts or datafication of HR by LinkedIn and others. Alternative examples are diverse and include aspects of the built environment, and design via engineering and or other tools that tie data to formal, functional or other physical media outcomes. Data collection and -processing for optimal control (e.g. shape optimization) is an example.


Human resources
Data obtained from mobile phones, apps or social media usage is used to identify potential employees and their specific characteristics such as risk taking profile and personality. This data will replace personality tests. Rather using the traditional personality tests or the exams that measure the analytical thinking, using the data obtained through datafication will change existing exam providers. Also, with this data new personality measures will be developed.[4][5]
Insurance and Banking
Data is used to understand an individual's risk profile and likelihood to pay a loan.
Customer relationship management
Various industries are using datafication to understand their customers better and create appropriate triggers based on each customer's personality and behaviour. This data is obtained from the language and tone a person uses in emails, phone calls or social medias.[6]
Street lamps in Amsterdam have been upgraded to allow municipal councils to dim the lights based on pedestrian usage.[7]
Smart city
Through the data obtained from the sensors that are implemented into the smart city, issues that can arise might be noticed and tackled in areas such as transportation, waste management, logistics, and energy. On the basis of real-time data, commuters could change their routes when there is a traffic jam. With the sensors that can measure air and water quality, cities can not only gain a more detailed understanding of the pollution levels, but may also enact new environmental regulations based on real-time data.[8]

See also[edit]


  1. ^ Cukier, Kenneth; Mayer-Schoenberger, Viktor (2013). "The Rise of Big Data". Foreign Affairs (May/June): 28–40. Retrieved 24 January 2014.
  2. ^ O'Neil, Cathy; Schutt, Rachel (2013). Doing Data Science. O’Reilly Media. p. 406. ISBN 978-1-4493-5865-5.
  3. ^ Biltgen, Patrick; Ryan, Stephen (1 January 2016). Activity-Based Intelligence: Principles and Applications (1 ed.). Norwood, MA: Artech House. p. 151. ISBN 978-1-60807-876-9. Retrieved 6 May 2017.
  4. ^ Moore, Melissa. "Turning Personality Into Data". Mattersight, The Chemistry of Conversation. Mattersight Corporation. Archived from the original on 11 November 2017. Retrieved 5 May 2017.
  5. ^
  6. ^ Moore, Melissa. "Turning Personality Into Data". Mattersight, The chemistry of Conversation. Mattersight Corporation. Archived from the original on 11 November 2017. Retrieved 5 May 2017.
  7. ^ Amsterdam Smart City. "Amsterdam Smart City ~ Climate Street". Retrieved 30 May 2015.
  8. ^

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